There is rapidly growing interest in extending the capabilities of image guided machining and cutting techniques and to adapting such techniques to unconventional areas such as surgery. Computed-assisted and robotic-assisted machining, and in particular computer-assisted and robotic-assisted surgery, requires accurate registration of a 3D image, typically computed tomography (CT) images, to intra-operative data collected by a pointing or other detecting and locating device. An impediment to successful registration is that the accuracy achievable with laboratory phantoms cannot be transferred into a machine shop or clinical setting: the phantoms and the methods used to isolate their locations are incompatible with normal machine shop or surgical practise.
Some current computer-assisted orthopaedic systems and robotic neurosurgery systems use large invasive markers that are implanted pre-operatively, under anaesthetic, or attempt to identify natural landmarks. ACT scan is then taken, and the images are processed semi-automatically to estimate the marker or landmarks locations. In surgery, the markers or landmarks are touched by a 3-D sensing apparatus, and point to point registration is performed. The best registration these approaches can regularly provide is .+-.2 mm, which is generally considered too imprecise for such procedures as knee surgery where there is a need for registration to be within .+-.1 mm in position and .+-.1.degree. in rotation. It has been found that misplacement of prosthetic knee components by only 2.5 mm can severely affect the range of flexion and other kinematic variables. Furthermore, the placement of the relatively large markers can often cause pain to the patient and it is unusual for such markers to be left in place permanently.
There is, therefore, a need for a less invasive, more accurate, registration technique for these surgical and other applications.